code: def emformer_hubert_model(
      extractor_input_dim: int,
      extractor_output_dim: int,
      extractor_use_bias: bool,
      extractor_stride: int,
      encoder_input_dim: int,
      encoder_output_dim: int,
      encoder_num_heads: int,
      encoder_ffn_dim: int,
      encoder_num_layers: int,
      encoder_segment_length: int,
      encoder_left_context_length: int,
      encoder_right_context_length: int,
      encoder_dropout: float,
      encoder_activation: str,
      encoder_max_memory_size: int,
      encoder_weight_init_scale_strategy: Optional[str],
      encoder_tanh_on_mem: bool,
      aux_num_out: Optional[int],
  ) -> Wav2Vec2Model:
      """Build a custom Emformer HuBERT model.
  
      Args:
          extractor_input_dim (int): The input dimension for feature extractor.
          extractor_output_dim (int): The output dimension after feature extractor.
          extractor_use_bias (bool): If ``True``, enable bias parameter in the linear layer of feature extractor.
          extractor_stride (int): Number of frames to merge for the output frame in feature extractor.
          encoder_input_dim (int): The input dimension for Emformer layer.
          encoder_output_dim (int): The output dimension after EmformerEncoder.
          encoder_num_heads (int): Number of attention heads in each Emformer layer.
          encoder_ffn_dim (int): Hidden layer dimension of feedforward network in Emformer.
          encoder_num_layers (int): Number of Emformer layers to instantiate.
          encoder_segment_length (int): Length of each input segment.
          encoder_left_context_length (int): Length of left context.
          encoder_right_context_length (int): Length of right context.
          encoder_dropout (float): Dropout probability.
          encoder_activation (str): Activation function to use in each Emformer layer's
              feedforward network. Must be one of ("relu", "gelu", "silu").
          encoder_max_memory_size (int): Maximum number of memory elements to use.
          encoder_weight_init_scale_strategy (str or None): Per-layer weight initialization scaling
              strategy. Must be one of ("depthwise", "constant", ``None``).
          encoder_tanh_on_mem (bool): If ``True``, applies tanh to memory elements.
          aux_num_out (int or None):
              When provided, attach an extra linear layer on top of encoder, which can be
              used for fine-tuning.
  
      Returns:
          Wav2Vec2Model:
              The resulting :py:class:`torchaudio.models.Wav2Vec2Model` model
              with a :py:class:`torchaudio.models.Emformer` encoder.
      """
      feature_extractor = _get_emformer_feature_extractor(
          extractor_input_dim,
          extractor_output_dim,
          extractor_use_bias,
          extractor_stride,
      )
      emformer = _get_emformer_encoder(
          encoder_input_dim,
          encoder_output_dim,
          encoder_num_heads,
          encoder_ffn_dim,
          encoder_num_layers,
          encoder_segment_length,
          encoder_left_context_length,
          encoder_right_context_length,
          encoder_dropout,
          encoder_activation,
          encoder_max_memory_size,
          encoder_weight_init_scale_strategy,
          encoder_tanh_on_mem,
      )
      aux = None
      if aux_num_out is not None:
          aux = torch.nn.Linear(
              in_features=encoder_output_dim, out_features=aux_num_out
          )
      return Wav2Vec2Model(feature_extractor, emformer, aux)
  
file_path: audio/src/torchaudio/prototype/models/_emformer_hubert.py
imports: from typing import List, Optional, Tuple
  import torch
  from torchaudio.models import Wav2Vec2Model
  from torchaudio.models.emformer import Emformer
  from torchaudio.models.rnnt import _TimeReduction
label_desc: Use image node_id 3 for calling a global function with example usage: emformer_hubert_model(extractor_input_dim, extractor_output_dim, extractor_use_bias, extractor_stride, encoder_input_dim, encoder_output_dim, encoder_num_heads, encoder_ffn_dim, encoder_num_layers, encoder_segment_length, encoder_left_context_length, encoder_right_context_length, encoder_dropout, encoder_activation, encoder_max_memory_size, encoder_weight_init_scale_strategy, encoder_tanh_on_mem, aux_num_out) and returns: Wav2Vec2Model